A smartphone Chatbot application to optimize monitoring of older patients with cancer. Piau Antoine,Crissey Rachel,Brechemier Delphine,Balardy Laurent,Nourhashemi Fati International journal of medical informatics BACKGROUND:Almost two thirds of patients diagnosed with cancer are age 65 years or older. In order to follow up on older patients with cancer receiving chemotherapy at home, we implemented remote phone monitoring conducted by skilled oncology nurses. However, given the rising number of patients assessed and the limited time that hospital professionals can spend on their patients after discharge, we needed to modernize this program. In this paper we present the preliminary results and the ongoing evaluation. METHOD:We implemented a semi-automated messaging application to upgrade the current follow-up procedures. The primary aim is to collect patient's key data over time and to free up nurses' time so that during phone calls they can focus on education and support. The Chatbot feasibility was assessed in a sub-sample of unselected patients before its wider dissemination and pragmatic evaluation. MAIN RESULTS:During the first deployment period, 9 unselected patients benefited from the Chatbot (mean 83 y.o.) with a total of 52 completed remote evaluations. Each participant answered 6 questionnaires over 7 weeks with an 86% compliance rate. The average completion time for the questionnaires was 3.5 min and the answer rate was 100%. The 'free text' field was used in 58% of the questionnaires. The Chatbot solution is currently proposed to all eligible patients thanks to the regional cancer network support. We are measuring acceptability, health outcomes and health network impact. DISCUSSION AND CONCLUSION:The results of this first phase are encouraging. The integration of the solution into the health care organization was feasible and acceptable. Moreover, the answers revealed serious health (e.g. fever) or adherence (e.g. blood test) issues that require timely interventions. The major strength of this solution is to rely on end-users' current knowledge of technologies (text-messaging), which allows a seamless integration into a complex clinical network. 10.1016/j.ijmedinf.2019.05.013

Effectiveness of the Medical Chatbot PROSCA to Inform Patients About Prostate Cancer: Results of a Randomized Controlled Trial. European urology open science Background and objective:Artificial intelligence (AI)-powered conversational agents are increasingly finding application in health care, as these can provide patient education at any time. However, their effectiveness in medical settings remains largely unexplored. This study aimed to assess the impact of the chatbot "PROState cancer Conversational Agent" (PROSCA), which was trained to provide validated support from diagnostic tests to treatment options for men facing prostate cancer (PC) diagnosis. Methods:The chatbot PROSCA, developed by urologists at Heidelberg University Hospital and SAP SE, was evaluated through a randomized controlled trial (RCT). Patients were assigned to either the chatbot group, receiving additional access to PROSCA alongside standard information by urologists, or the control group (1:1), receiving standard information. A total of 112 men were included, of whom 103 gave feedback at study completion. Key findings and limitations:Over time, patients' information needs decreased significantly more in the chatbot group than in the control group ( = 0.035). In the chatbot group, 43/54 men (79.6%) used PROSCA, and all of them found it easy to use. Of the men, 71.4% agreed that the chatbot improved their informedness about PC and 90.7% would like to use PROSCA again. Limitations are study sample size, single-center design, and specific clinical application. Conclusions and clinical implications:With the introduction of the PROSCA chatbot, we created and evaluated an innovative, evidence-based AI health information tool as an additional source of information for PC. Our RCT results showed significant benefits of the chatbot in reducing patients' information needs and enhancing their understanding of PC. This easy-to-use AI tool provides accurate, timely, and accessible support, demonstrating its value in the PC diagnosis process. Future steps include further customization of the chatbot's responses and integration with the existing health care systems to maximize its impact on patient outcomes. Patient summary:This study evaluated an artificial intelligence-powered chatbot-PROSCA, a digital tool designed to support men facing prostate cancer diagnosis by providing validated information from diagnosis to treatment. Results showed that patients who used the chatbot as an additional tool felt better informed than those who received standard information from urologists. The majority of users appreciated the ease of use of the chatbot and expressed a desire to use it again; this suggests that PROSCA could be a valuable resource to improve patient understanding in prostate cancer diagnosis. 10.1016/j.euros.2024.08.022

Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study. Journal of medical Internet research BACKGROUND:Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. OBJECTIVE:Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. METHODS:Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. RESULTS:The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: "Anytime, anywhere"; "In addition, not instead"; and "Trustworthy and true." All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. CONCLUSIONS:Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling. 10.2196/46571

Triangle of Trust in Cancer Care? The Physician, the Patient, and Artificial Intelligence Chatbot. Cancer biotherapy & radiopharmaceuticals Trust, as a philosophic paradigm, is predominantly interpersonal, between human beings, and is differentiated from reliance. Can a person trust an inhumane amoral agent, such as a large language model artificial intelligence (AI) chatbot, to manifest the goodwill and willingness normally required in order for it to be deemed trustworthy? This article explores the relationship between the cancer patient, their physician, and AI chatbot in a proposed tripartite, consultative, personalized approach to shared-care in precision molecular oncology. It examines the nature of trust between human agents and machines. It also contemplates AI-enhanced technical precision in state-of-the-art cancer management, complemented by trustworthy, holistic clinical care by a physician, for each individual patient. " "" " Peter Lee, Microsoft Research 2023. 10.1089/cbr.2023.0112

An artificial intelligence-based chatbot for prostate cancer education: Design and patient evaluation study. Digital health Introduction:Artificial intelligence (AI) is increasingly used in healthcare. AI-based chatbots can act as automated conversational agents, capable of promoting health and providing education at any time. The objective of this study was to develop and evaluate a user-friendly medical chatbot (prostate cancer communication assistant (PROSCA)) for provisioning patient information about early detection of prostate cancer (PC). Methods:The chatbot was developed to provide information on prostate diseases, diagnostic tests for PC detection, stages, and treatment options. Ten men aged 49 to 81 years with suspicion of PC were enrolled in this study. Nine of ten patients used the chatbot during the evaluation period and filled out the questionnaires on usage and usability, perceived benefits, and potential for improvement. Results:The chatbot was straightforward to use, with 78% of users not needing any assistance during usage. In total, 89% of the chatbot users in the study experienced a clear to moderate increase in knowledge about PC through the chatbot. All study participants who tested the chatbot would like to re-use a medical chatbot in the future and support the use of chatbots in the clinical routine. Conclusions:Through the introduction of the chatbot PROSCA, we created and evaluated an innovative evidence-based health information tool in the field of PC, allowing targeted support for doctor-patient communication and offering great potential in raising awareness, patient education, and support. Our study revealed that a medical chatbot in the field of early PC detection is readily accepted and benefits patients as an additional informative tool. 10.1177/20552076231173304